Antipeptide Immunocapture with In-Sample Calibration Curve Strategy for Sensitive and Robust LC-MS/MS Bioanalysis of Clinical Protein Biomarkers in Formalin-Fixed Paraffin-Embedded Tumor Tissues

Abstract

Despite huge promises, bioanalysis of protein biomarkers in formalin-fixed paraffin-embedded (FFPE) tissues by liquid chromatography-tandem mass spectrometry (LC-MS/MS) for clinical applications is still very challenging. Here, we describe a sensitive and robust LC-MS/MS assay to quantify clinical protein biomarkers in FFPE tumor sections using automated antipeptide antibody immunocapture followed by in-sample calibration curve (ISCC) strategy with multiple isotopologue reaction monitoring (MIRM) technique. ISCC approach with MIRM of stable isotopically labeled (SIL) peptides eliminated the need for authentic matrices for external calibration curves, overcame the matrix effects, and validated the quantification range in each individual sample. Specifically, after deparaffinization, rehydration, antigen retrieval, and homogenization, the protein analytes in FFPE tumor tissues were spiked with a known concentration of one SIL peptide for each analyte, followed by trypsin digestion and antipeptide immunocapture enrichment prior to MIRM-ISCC-based LC-MS/MS analysis. This approach has been successfully used for sensitive quantification of programmed cell death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) in 15 representative FFPE tumor samples from lung, colorectal, and head and neck cancer patients. Except for one sample, PD-L1 and PD-1 in all samples were quantifiable using this assay with concentrations of 27.85-798.43 (amol/μg protein) for PD-L1 and 16.96-129.89 (amol/μg protein) for PD-1. These results were generally in agreement with the immunohistochemistry (IHC) data but with some exceptions. This approach demonstrated the feasibility to quantify low abundant protein biomarkers in FFPE tissues with improved sensitivity, specificity, and robustness and showed great potential as an orthogonal analytical approach to IHC for clinical applications.